Abstract

Chen et al. [J. Acoust. Soc. Am. 131, 2987–2998 (2012)] evaluated the effectiveness of an algorithm for enhancing spectral changes over time in improving the intelligibility of speech in background sounds for hearing-impaired subjects. The processing improved intelligibility for speech in steady speech-spectrum noise (SSN) but tended to impair intelligibility in a background of two-talker speech(TTS). Large individual differences were found. The present study assessed whether the effectiveness of the algorithm was improved when the parameters that controlled the degree and type of enhancement were chosen individually for each subject, using a genetic algorithm based on subjective preferences for speech clarity. The parameter values selected by the genetic algorithm varied markedly across subjects. Speech intelligibility was measured for unprocessed stimuli and stimuli processed using the selected parameters, with SSN and TTS maskers and two signal-to-masker ratios (SMRs) for each subject. The intelligibility of speech in the SSN masker at the lower SMR was improved about 14 percentage points by the processing. The overall improvement produced by the processing was significantly larger than the improvement observed in the previous study when the parameter values were fixed across subjects, indicating that use of the genetic algorithm was beneficial.

Received 25 March 2012Revised 05 March 2013Accepted 20 March 2013Published online 06 May 2013

Acknowledgments:

This work was supported by a Newton International Fellowship, follow-on funding from the Royal Society and the Royal Academy of Engineering, Deafness Research UK, and Starkey. T.B. and B.C.J.M. were supported by the MRC (Grant No. G0701870). Thanks to Michael Stone for assistance with the experimental set up. The code for the GA was written by Eric Durant and was supplied by Starkey. We thank two anonymous reviewers for helpful comments on an earlier version of this paper.